Extracting feature fusion and co-saliency clusters using transfer learning techniques for improving remote sensing scene classification
To attribute the semantics to land cover, scene classification of very high-resolution (VHR)
imagery comprises many possible applications in diverse domains. Conventional remote …
imagery comprises many possible applications in diverse domains. Conventional remote …
Local feature matching from detector-based to detector-free: a survey
Y Liao, Y Di, K Zhu, H Zhou, M Lu, Y Zhang, Q Duan… - Applied …, 2024 - Springer
Local feature matching has been a critical task in computer vision applications. In the early
days of computer vision, local feature matching relied heavily on detector-based methods …
days of computer vision, local feature matching relied heavily on detector-based methods …
A critical survey of GEOBIA methods for forest image detection and classification
C Kwenda, MV Gwetu, JV Fonou-Dombeu - Geocarto International, 2023 - Taylor & Francis
Modern earth observation sensors have revolutionized the remote sensing community by
improving remote sensing image quality. However, Pixel-based image analysis methods …
improving remote sensing image quality. However, Pixel-based image analysis methods …
Remote sensing traffic scene retrieval based on learning control algorithm for robot multimodal sensing information fusion and human-machine interaction and …
In light of advancing socio-economic development and urban infrastructure, urban traffic
congestion and accidents have become pressing issues. High-resolution remote sensing …
congestion and accidents have become pressing issues. High-resolution remote sensing …
SingleS2R: Single sample driven Sim-to-Real transfer for Multi-Source Visual-Tactile Information Understanding using multi-scale vision transformers
Due to variations in light transmission and wear on the contact head, existing visual-tactile
dataset building methods typically require a large amount of real-world data, making the …
dataset building methods typically require a large amount of real-world data, making the …
Local feature acquisition and global context understanding network for very high-resolution land cover classification
Z Li, J Hu, K Wu, J Miao, Z Zhao, J Wu - Scientific Reports, 2024 - nature.com
Very high-resolution remote sensing images hold promising applications in ground
observation tasks, paving the way for highly competitive solutions using image processing …
observation tasks, paving the way for highly competitive solutions using image processing …
Selective Task offloading for Maximum Inference Accuracy and Energy efficient Real-Time IoT Sensing Systems
The recent advancements in small-size inference models facilitated AI deployment on the
edge. However, the limited resource nature of edge devices poses new challenges …
edge. However, the limited resource nature of edge devices poses new challenges …
Classification and Recognition of Building Appearance Based on Optimized Gradient-Boosted Decision Tree Algorithm
M Hu, L Guo, J Liu, Y Song - Sensors, 2023 - mdpi.com
There are high concentrations of urban spaces and increasingly complex land use types.
Providing an efficient and scientific identification of building types has become a major …
Providing an efficient and scientific identification of building types has become a major …
A cross-attention integrated shifted window transformer for remote sensing image scene recognition with limited data
K Li, Y Xue, J Zhao, H Li… - Journal of Applied Remote …, 2024 - spiedigitallibrary.org
The aim of remote sensing image scene recognition is to label a set of semantic categories
based on their contents, and recognition for remote sensing images has a wide range of …
based on their contents, and recognition for remote sensing images has a wide range of …
Towards the Interpretation of Multi-Label Image Classification Using Transformers and Fuzzy Cognitive Maps
G Sovatzidi, MD Vasilakakis… - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
Multi-label image classification is a challenging task in the field of computer vision. Recently,
many deep learning approaches have been proposed to deal with this task; however …
many deep learning approaches have been proposed to deal with this task; however …